Surface plasmon resonance (SPR) is a widely used, affinity based, label-free biophysical technique to investigate biomolecular interactions. The information gained using SPR can be applied in a multitude of ways. For example, SPR can be used in the medical and pharmaceutical industries in discovering and developing new drugs, studying protein-protein and protein-DNA interactions, and understanding the adsorption of chemical molecules. Surface plasmon resonance can also be used in the food and beverage industry to ensure safety and quality control (e.g., to test for veterinary drug residues in foodstuffs and to test for the presence of genetically modified organisms). However, applications of SPR often require a difficult process of developing models and extracting rate constants.
Obtaining accurate models and rate constants enable a better understanding of the interactions taking place, better predictions and analysis, as well as reduced computing resources. In turn, this leads to SPR being a more effective tool, regardless of the particular industry in which it is applied. Therefore, there is always a need for new and improved ways to analyze SPR data, provide more accurate models, and extract more accurate rate constants.